Adaptive robust force control method and device for wearable waist-assisted exoskeleton

Abstract

The present invention relates to the field of exoskeleton control technology, and discloses an adaptive robust force control method and device for a wearable waist-assisted exoskeleton. The adaptive robust force control method comprises: initializing the waist-assisted exoskeleton; establishing a physical model and converting it into a state equation; extracting relevant expressions in the physical model to obtain dynamic equations related to control input and output; taking the angles, angular velocities, angular accelerations of various joints of the human body and the hip joints of the exoskeleton, and the torque at the human hip joint as input quantities, and outputting the motor driving torque; converting the motor driving torque into the output torque of the motor controlled by the control current to drive the rotation of the waist-assisted exoskeleton joints. The control method used in the present invention effectively overcomes the influence of the multi-joint strong coupling and model uncertainty of the human-exoskeleton system, and the control algorithm can adapt to the change of load, so as to achieve the good assisting effect of the waist-assisted exoskeleton on people carrying heavy objects, and has a strong application value.

Description

Technical Field

[0001] The present invention relates to the field of exoskeleton control technology, and in particular to an adaptive robust force control method for a wearable waist-assisted exoskeleton, and an adaptive robust force control device for a wearable waist-assisted exoskeleton using the control method. Background Art

[0002] In work scenarios such as construction sites, logistics companies, shipyards, and aircraft production workshops, workers often need to bend over repeatedly to carry heavy objects. After a long period of carrying, many workers will suffer serious back injuries. The waist-assisted exoskeleton is a wearable robotic system that uses the exoskeleton power-assist system to pull the worker's back to stand upright, and transfers part of the load to the legs through a mechanical structure. When workers bend over to carry heavy objects, the waist-assisted exoskeleton can effectively relieve the pressure on the spine and reduce damage to the workers' back muscles, thereby improving work efficiency. Although there have been some successful cases of applying waist-assisted exoskeletons to the industrial field, the existing waist-assisted exoskeletons still have shortcomings in control performance.

[0003] The existing waist-assisted exoskeleton dynamics modeling methods are overly simplified. Usually, the waist is simplified into a simple pendulum model including the hip joint and the back, while ignoring the influence of the lower and upper limbs of the human body. The simplified dynamics modeling method makes the model very different from the actual system. It is difficult for the controller designed based on the simplified model to achieve a good power-assisting effect. In addition, the waist-assisted exoskeleton system itself has strong coupling nonlinearity and various model uncertainties. For example, the mass of the load often changes during the handling process. The existing waist-assisted exoskeleton control methods only involve the preliminary control of the exoskeleton, and cannot handle the influence of model uncertainties such as load changes, and the robustness of the algorithm is not strong. Summary of the invention

[0004] Based on this, it is necessary to provide an adaptive robust force control method and device for a wearable waist-assisted exoskeleton to address the problem of weak system robustness of existing waist-assisted exoskeleton control methods.

[0005] The present invention is implemented by the following technical solutions:

[0006] In a first aspect, the present invention discloses an adaptive robust force control method for a wearable waist-assisted exoskeleton, which is used to control the waist-assisted exoskeleton.

[0007] The waist-assisted exoskeleton includes: a backboard, a back strap, a waist strap, an exoskeleton hip joint, several posture sensors, an electromyographic sensor, and a real-time controller.

[0008] The back strap is fixed to the upper end of the backboard and is used to bind the back of the human body. The waist strap is fixed to the lower end of the backboard and is used to bind the waist of the human body. Two groups of exoskeleton hip joints are set, and are respectively set on both sides of the backboard. The exoskeleton hip joint includes a thigh rod, a harmonic reducer, a hip joint motor, a waist connector, and a motor rotary encoder. The outer ring of the harmonic reducer is connected to the thigh rod. The rotor of the hip joint motor is connected to the inner ring of the harmonic reducer, and the stator is connected to the outer ring of the harmonic reducer. One end of the waist connector is connected to the inner ring of the harmonic reducer, and the other end is connected to the backboard. The motor rotary encoder is installed on the hip joint motor. Several posture sensors are set on the thigh rod, the backboard, the human calf, the human thigh, the human trunk, and the human upper limbs. The electromyographic sensor is set on the human waist. The real-time controller is installed on the backboard. The real-time controller is electrically connected to the hip joint motor, the motor rotary encoder, the posture sensor, and the electromyographic sensor.

[0009] The adaptive robust force control method includes the following steps:

[0010] S1, initialize the sampling cycle of the real-time controller; initialize several posture sensors and electromyographic sensors, and adjust the sensor values ​​to zero; rotate the thigh rod and backboard to the vertical position, and initialize the motor rotary encoder and adjust the motor rotary encoder value to zero;

[0011] S2, establishing a physical model of the waist-assisted exoskeleton and converting the physical model into a state equation; wherein the physical model includes a human-exoskeleton coupling system dynamics model, a human-machine interface model, and a complete constraint model provided by the wearer;

[0012] S3, obtaining the angle, angular velocity, angular acceleration of each joint of the human body, and the torque at the human hip joint, obtaining the angle, angular velocity, and angular acceleration of the exoskeleton hip joint, and calculating the motor driving torque;

[0013] S4, converts the motor driving torque into the control current of the corresponding hip joint motor, controls the output torque of the corresponding hip joint motor by controlling the current, drives the thigh rod to rotate relative to the back plate, and realizes the movement of the waist-assisted exoskeleton.

[0014] The implementation of the adaptive robust force control method of the wearable waist-assisted exoskeleton is based on the method or process of an embodiment of the present disclosure.

[0015] In a second aspect, the present invention discloses an adaptive robust force control device for a wearable waist-assisted exoskeleton, which uses the adaptive robust force control method for a wearable waist-assisted exoskeleton disclosed in the first aspect.

[0016] The adaptive robust force control device of the wearable waist-assisted exoskeleton includes: an initialization module, a model building module, a data acquisition and processing module, a conversion module, and an output module.

[0017] The initialization module includes submodule 1, submodule 2, submodule 3, and submodule 4. Submodule 1 is used to initialize the sampling period of the real-time controller. Submodule 2 is used to initialize several posture sensors and adjust the posture sensor values ​​to zero. Submodule 3 is used to rotate the thigh rod and backboard to a vertical position, initialize the motor rotary encoder, and adjust the motor rotary encoder value to zero. Submodule 4 is used to initialize the electromyographic sensor and adjust the electromyographic sensor value to zero.

[0018] The model building module is used to build the physical model of the waist-assisted exoskeleton and convert the physical model into a state equation. The physical model includes a human-exoskeleton coupling dynamics model, a human-machine interface model, and a complete constraint model provided by the wearer.

[0019] The data acquisition and processing module is used to obtain the angle, angular velocity, angular acceleration of each joint of the human body, and the torque at the human hip joint, obtain the angle, angular velocity, angular acceleration of the exoskeleton hip joint, and calculate the motor driving torque.

[0020] The conversion module is used to convert the motor driving torque into the control current of the corresponding hip joint motor.

[0021] The output module is used to control the output torque of the corresponding hip joint motor by controlling the current, driving the thigh rod to rotate relative to the back plate, thereby realizing the movement of the waist-assisted exoskeleton.

[0022] The implementation of the adaptive robust force control device of the wearable waist-assisted exoskeleton is based on the method or process of an embodiment of the present disclosure.

[0023] In a third aspect, the present invention discloses a computer terminal, which includes a memory, a processor, and a computer program in the memory that can be run on the processor. When the processor executes the program, the adaptive robust force control method of the wearable waist-assisted exoskeleton according to the first aspect is implemented.

[0024] The present invention discloses a readable storage medium. The readable storage medium stores computer program instructions, and when the computer program instructions are read and run by a processor, the adaptive robust force control method of the wearable waist-assisted exoskeleton as described in the first aspect is executed.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. The sensor of the present invention is composed of a posture sensor, an electromyographic sensor and a motor rotary encoder to achieve more effective and reliable human-machine interaction; moreover, in view of the force enhancement and following problems of the waist-assisted exoskeleton, the complete constraints provided by the wearer are considered to transform the five-degree-of-freedom human-machine coupled waist-assisted exoskeleton system into a single-degree-of-freedom system.

[0027] 2. The present invention utilizes an adaptive robust control algorithm (ARC) to perform force control, so that the waist-assisted exoskeleton system can adapt to changes in load and has strong robustness to various model uncertainties, so that the wearer's waist muscle output force tends to a preset minimum value, reducing the burden on the wearer's waist and having strong practical application value.

[0028] 3. The present invention fully considers the control of the wearer over the exoskeleton, is effective and reliable in human-machine interaction, and has the characteristics of rapid response to human movement intentions. The present invention regards the exoskeleton wearer as a participant in system control. In the walking plane, the wearer can ensure the balance of the entire system when walking forward and backward and bending over, and avoid the exoskeleton from falling. At the same time, the control method is simple, easy to implement in engineering, and flexible to control. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 This is a schematic diagram of the overall shape and structure of a waist-assisted exoskeleton used in the adaptive robust force control method of a wearable waist-assisted exoskeleton according to Example 1 of the present invention;

[0031] Figure 2 for Figure 1 Back view of the wearable waist-assisted exoskeleton in;

[0032] Figure 3 for Figure 1 Side view of the wearable waist-assisted exoskeleton in;

[0033] Figure 4 This is a control flow chart of an adaptive robust force control method for a wearable waist-assisted exoskeleton according to Embodiment 1 of the present invention;

[0034] Figure 5 This is a control block diagram of an adaptive robust force control method for a wearable waist-assisted exoskeleton according to Embodiment 1 of the present invention;

[0035] Figure 6 is a simulation result diagram of embodiment 1 of the present invention under no-load condition;

[0036] Figure 7 This is a simulation result diagram of Example 1 of the present invention when the load mass is 20 kg.

[0037] In the accompanying drawings, the components represented by the reference numerals are listed as follows:

[0038] 1. Thigh rod, 2. Harmonic reducer, 3. Motor, 4. Waist connector, 5. Waist strap, 6. Back strap, 7. Back plate, 8. Motor rotary encoder, 9. Posture sensor, 10. Real-time controller. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] It should be noted that when a component is referred to as being "mounted on" another component, it can be directly on the other component or there can be a component centered. When a component is considered to be "set on" another component, it can be directly set on the other component or there can be a component centered. When a component is considered to be "fixed to" another component, it can be directly fixed to the other component or there can be a component centered.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "or / and" used herein includes any and all combinations of one or more of the related listed items.

[0042] Example 1

[0043] This embodiment 1 provides an adaptive robust force control method for a wearable waist-assisted exoskeleton, which is used to control a wearable waist-assisted exoskeleton.

[0044] See also Figure 1 , 2 , 3 is a structural diagram of the wearable waist-assisted exoskeleton, and the components shown in the figure are: thigh rod 1, harmonic reducer 2, motor 3, waist connector 4, waist strap 5, back strap 6, backboard 7, motor rotary encoder 8, posture sensor 9, real-time controller 10, and some components are not drawn because they are installed on the human body.

[0045] In this embodiment 1, the waist-assisted exoskeleton includes: a back plate 7, a back strap 6, a waist strap 5, an exoskeleton hip joint, a plurality of posture sensors 9, an electromyographic sensor (not shown), and a real-time controller 10.

[0046] The back strap 6 is fixed to the upper end of the back plate and is used to bind the back of the human body and tighten the back of the human body when wearing the body.

[0047] The waist strap 5 is fixed to the lower end of the back plate and is used to bind the waist of the human body and tighten the waist of the human body when worn.

[0048] Two groups of exoskeleton hip joints are provided, and are respectively arranged on both sides of the backboard. The exoskeleton hip joint includes a thigh rod 1, a harmonic reducer 2, a hip joint motor 3, a waist connector 4, and a motor rotary encoder 8. One end of the thigh rod 1 is fixedly connected to the outer ring of the harmonic reducer 2, and the other end fits the human thigh when worn. The hip joint motor 3 adopts an RMD-L type disc motor, whose rotor is connected to the inner ring of the harmonic reducer 2, and the stator is connected to the outer ring of the harmonic reducer 2. One end of the waist connector 4 is connected to the inner ring of the harmonic reducer 2, and the other end is connected to the backboard 7. The motor rotary encoder 8 is installed on the motor 3 to detect the rotation angle and angular velocity of the hip joint motor 3. The posture sensor 9 adopts a JY61 posture sensor, which is installed on the thigh rod 1, the backboard 7, the human calf, the human thigh, the human trunk, and the human upper limbs to detect the corresponding angle, angular velocity and angular acceleration. The human waist is attached with an electromyographic sensor to detect the torque at the human hip joint. The real-time controller 10 is mounted on the back plate 7. The real-time controller 10 adopts an Arduino controller and is electrically connected to the hip joint motor 3, the motor rotary encoder 8, the posture sensor 9, the myoelectric sensor and other devices.

[0049] See also Figure 4 , the adaptive robust force control method mainly includes the following steps:

[0050] S1, initialize the sampling cycle of the real-time controller; initialize several posture sensors and electromyography sensors, and adjust the sensor values ​​to zero; rotate the thigh rod and backboard to the vertical position, and initialize the motor rotary encoder and adjust the motor rotary encoder value to zero.

[0051] This step is to initialize the waist-assisted exoskeleton.

[0052] S2, establish a physical model of the waist-assisted exoskeleton and convert the physical model into a state equation; wherein the physical model includes a human-exoskeleton coupling system dynamics model, a human-machine interface model, and a complete constraint model provided by the wearer.

[0053] This step is to convert the five-degree-of-freedom human-machine coupled waist-assisted exoskeleton system into a single-degree-of-freedom system. The five degrees of freedom include: one degree of freedom corresponding to the human ankle joint, one degree of freedom corresponding to the human knee joint, one degree of freedom corresponding to the human hip joint, one degree of freedom corresponding to the human shoulder joint, and one degree of freedom corresponding to the exoskeleton hip joint.

[0054] (1) The dynamic model of the human-exoskeleton coupling system is:

[0055]

[0056] Where q = [q1 q2 q3 q4 q5] T , q1, q2, q3, q4, and q5 are the rotation angles of the human ankle joint, human knee joint, human hip joint, human shoulder joint, and exoskeleton hip joint, respectively;

[0057] τ=[τ1 τ2 τ3 τ4 τ act ] T , τ1, τ2, τ3, τ4 are the applied moments of the human ankle joint, human knee joint, human hip joint, and human shoulder joint, respectively, τ act is the driving torque of the exoskeleton hip joint;

[0058] F b =[F bx F by F bz ] T is the human-machine force, F bx 、F by 、F bx They represent the components of the human-machine force in the x, y, and z directions respectively;

[0059] J h ∈R 3*5 is the Jacobian matrix of the human back at the back contact point;

[0060] J e ∈R 3*5 is the Jacobian matrix of the back plate at the back contact;

[0061] M(q)∈R 5*5 is the inertia matrix of the human-exoskeleton coupling system;

[0062] Centrifugal force and Coriolis force matrix for human-exoskeleton coupling system;

[0063] G(q)∈R 5 Gravity matrix for the human-exoskeleton coupling system.

[0064] (2) The human-machine interface model is:

[0065]

[0066] Where, K = diag{K x ,K y ,K z} is the equivalent spring stiffness, K x , Ky , K z Respectively represent the components of the equivalent spring stiffness in the x, y, and z directions;

[0067] C=diag{C x ,C y ,C z} is the damping coefficient of the equivalent damper, C x , C y , C z They represent the components of the equivalent damper damping coefficient in the x, y, and z directions respectively;

[0068] x h =[x hx x hy x hz ] T is the position of the person at the back contact point, x hx 、x hy They represent the position of the person at the back contact point in the x and y directions, respectively. hz It represents the rotation angle of the person around the z-axis at the back contact point;

[0069] x e =[x ex x ey x ez ] T The position of the exoskeleton at the back contact point for the waist assistance, x ex 、x ey They represent the x and y positions of the waist-assisted exoskeleton at the back contact point, respectively. ez It represents the rotation angle of the waist-assisted exoskeleton around the z-axis at the back contact point;

[0070] is the speed of the person at the back contact point, They represent the speed of the person in the x and y directions at the back contact point, represents the angular velocity of the person around the z-axis at the back contact point;

[0071] The speed of the exoskeleton at the back contact point for the waist, They represent the speed of the waist-assisted exoskeleton in the x and y directions at the back contact point, It represents the angular velocity of the waist-assisted exoskeleton around the z-axis at the back contact point;

[0072] Centrally model uncertainty and disturbances at the human-machine interface.

[0073] (3) The complete constraint model is:

[0074] q1=qhd1 (t),q2=q hd2 (t),q3=q hd3 (t),q4=q hd4 (t);

[0075] In the formula, q hd1 (t) represents the relationship between the human ankle joint angle and time t;

[0076] q hd2 (t) represents the relationship between the human knee joint angle and time t;

[0077] q hd3 (t) represents the relationship between the human hip joint angle and time t;

[0078] q hd4 (t) represents the relationship between the human shoulder joint angle and time t.

[0079] After the physical models of (1), (2), and (3) are established, the physical models need to be converted into state equations, that is, the relevant expressions in the physical models need to be extracted to obtain the dynamic equations related to the control input and output. This mainly includes the following steps:

[0080] S5.1, calculate τ3 and τ act relationship.

[0081] In order to obtain τ3 and τ act The relationship, specifically:

[0082] The first-order and second-order derivatives of the complete constraint model are:

[0083]

[0084]

[0085] According to the complete constraint model, the human-exoskeleton coupling system dynamics model and the human-machine interface model, we can find τ3 is:

[0086]

[0087]

[0088] Where M 51 ,M 52 ,M 53 ,M 54 ,M 55 They are the corresponding elements of the 5th row, 1st to 5th columns in M(q), U5 = [0 0 0 01], U3 = [0 0 1 0 0];

[0089] Transform the above formula and Substituting in, we get:

[0090]

[0091] In the formula,

[0092] M 31 ,M 32 ,M 33 ,M 34 They are the corresponding elements in the 3rd row and 1st to 4th columns in M(q);

[0093] C 31 ,C 32 ,C 33 ,C 34 They are The corresponding elements in the 3rd row, 1st to 4th columns;

[0094] C 51 ,C 52 They are The corresponding elements in the 5th row, 1st to 2nd columns;

[0095] G3 and G5 are the corresponding elements in the 3rd and 5th rows of G(q) respectively.

[0096] S5.2, let the state variable x1 = ∫τ3dτ, and let the concentrated model uncertainty be:

[0097] S5.3, the concentrated model uncertainty is divided into two parts: a constant and a time-varying function, and we get Δ 1n and Δ1 represent The constant part and the time-varying part.

[0098] S5.4, let θ = [J5 Y2 Δ 1n K x K y K z C x C y C z ] T ; Among them, J5 and Y2 are the system parameters of the waist-assisted exoskeleton.

[0099] S5.5, the state equation of the physical model of the waist-assisted exoskeleton is:

[0100]

[0101] in,

[0102] g is the acceleration due to gravity, c is 125tm=cos(q1+q2+q5-θ m ), θ m is the angle between the thigh bar and the human thigh;

[0103] S3, obtaining the angle, angular velocity, angular acceleration of each joint of the human body, and the torque at the human hip joint, obtaining the angle, angular velocity, angular acceleration of the exoskeleton hip joint, and calculating the motor driving torque.

[0104] This step is to obtain parameter values ​​through the posture sensor, motor rotary encoder, and electromyographic sensor to calculate the motor driving torque. In other words, the angles, angular velocities, angular accelerations of each joint of the human body and the hip joint of the exoskeleton, and the torque at the human hip joint are used as input, and the output is the motor driving torque.

[0105] The motor driving torque is equal to τ act In fact, this step is to get τ act , and τ act The following control objectives must be met.

[0106] Specifically, according to the state equation of the physical model of the waist-assisted exoskeleton, the control error is z1=x1-x 1d , where x 1d It is the integral of the desired human hip joint torque, which is generally a preset minimum value, such as 0, or a constant value approaching 0 (0.1, 0.01, etc.).

[0107] The control objective is to design τ act Make z1 approach 0, that is, z1 = x1-x 1d =0, in other words, x1=x 1d Since x1 = ∫τ3dτ, that is, let τ3 tend to a set constant value: Since x 1d The value is small, so τ3 is also small.

[0108] Assume τ act =τ acta +τ acts ,in τ acts =k1z1+τ actsn , is the desired human hip torque. Generally, k1 represents the gain value of linear feedback, τ actsn is the nonlinear feedback term; is an estimate of the actual value θ, and the estimated value The range is: for The minimum value of for The maximum value of

[0109] Adaptive Rate get:

[0110] in Γ1 is the adaptation rate matrix.

[0111] The mapping function is:

[0112]

[0113] In the formula, i is the independent variable;

[0114] τ actsn Two conditions must be met:

[0115]

[0116] In the formula, ε1 is a threshold and is any non-negative number.

[0117] S4, converts the motor driving torque into the control current of the corresponding hip joint motor, controls the output torque of the corresponding hip joint motor by controlling the current, drives the thigh rod to rotate relative to the back plate, and realizes the movement of the waist-assisted exoskeleton.

[0118] This step is to convert and control the output of the hip joint motor based on the motor driving torque, thereby realizing the control of the waist power-assisted exoskeleton. This step is an existing mature technology and will not be repeated here.

[0119] It should be noted that the real-time controller 10 can be designed to directly execute the above-mentioned adaptive robust force control method. Of course, a control unit can also be set on the waist-assisted exoskeleton, named as an adaptive robust force controller, for executing the above-mentioned adaptive robust force control method, such as Figure 5 shown.

[0120] In addition, the inventors also conducted simulation verification on the adaptive robust force control method, where:

[0121] x 1d The value is 0. The value is 0, k1 is 25; The initial value is Pick Pick Take Γ1=diag{0,0,200,0,0,0,0,0,0}, take ε1=1, take τ actsn =0, then the control target is that z1=x1=∫τ3dτ tends to 0, that is, to make τ3 tend to 0.

[0122] Simulation results see Figure 6 , Figure 7 , Figure 6 For no-load conditions, Figure 7 It is the case with load (load mass 20kg). It can be seen from the figure that the adaptive robust force control method can adapt to the load change and make τ3 tend to 0, that is, the waist muscle output force tends to 0, which reduces the burden on the wearer's waist and has strong practical application value.

[0123] Example 2

[0124] This embodiment 2 provides an adaptive robust force control device for a wearable waist-assisted exoskeleton. The adaptive robust force control device uses the adaptive robust force control method of embodiment 1.

[0125] The adaptive robust force control device of the wearable waist-assisted exoskeleton includes: an initialization module, a model building module, a data acquisition and processing module, a conversion module, and an output module.

[0126] The initialization module includes submodule 1, submodule 2, submodule 3, and submodule 4. Submodule 1 is used to initialize the sampling period of the real-time controller. The sampling period is generally set between 10 and 20 milliseconds. Submodule 2 is used to initialize several posture sensors and adjust the posture sensor values ​​to zero. Submodule 3 is used to rotate the thigh bar and backboard to a vertical position, initialize the motor rotary encoder, and adjust the motor rotary encoder value to zero. Submodule 4 is used to initialize the electromyographic sensor and adjust the electromyographic sensor value to zero.

[0127] The model building module is used to build the physical model of the waist-assisted exoskeleton and convert the physical model into a state equation. The physical model includes a human-exoskeleton coupling dynamics model, a human-machine interface model, and a complete constraint model provided by the wearer.

[0128] The data acquisition and processing module is used to obtain the angle, angular velocity, angular acceleration of each joint of the human body, and the torque at the human hip joint, obtain the angle, angular velocity, angular acceleration of the exoskeleton hip joint, and calculate the motor driving torque.

[0129] The conversion module is used to convert the motor driving torque into the control current of the corresponding hip joint motor.

[0130] The output module is used to control the output torque of the corresponding hip joint motor by controlling the current, driving the thigh rod to rotate relative to the back plate, thereby realizing the movement of the waist-assisted exoskeleton.

[0131] Example 3

[0132] This embodiment provides a computer terminal, which includes a memory, a processor, and a computer program in the memory that can be run on the processor. When the processor executes the program, the adaptive robust force control method of the wearable waist-assisted exoskeleton of embodiment 1 is implemented.

[0133] The method of Example 1 can be applied in the form of software, such as being designed as an independently running program and installed on a computer terminal, which can be a computer, a smart phone, a control system, and other IoT devices. The method of Example 1 can also be designed as an embedded running program and installed on a computer terminal, such as a single chip microcomputer.

[0134] Example 4

[0135] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the adaptive robust force control method for a wearable waist-assisted exoskeleton of embodiment 1 are implemented.

[0136] When the method of Example 1 is applied, it can be applied in the form of software, such as a program designed to be independently run on a computer-readable storage medium, where the computer-readable storage medium can be a USB flash drive, and the USB flash drive is designed to start the program of the entire method through an external trigger.

[0137] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0138] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. An adaptive robust force control method for a wearable waist-assisted exoskeleton, which is used to control the waist-assisted exoskeleton; The waist-assisted exoskeleton comprises: Back panel; The back strap is fixed to the upper end of the backboard and is used to bind the back of the human body; A waist strap, which is fixed to the lower end of the back plate and is used to bind the waist of the human body; An exoskeleton hip joint is provided with two groups, which are respectively arranged on both sides of a back plate; the exoskeleton hip joint comprises a thigh rod, a harmonic reducer, a hip joint motor, a waist connector, and a motor rotary encoder; the outer ring of the harmonic reducer is connected to the thigh rod; the rotor of the hip joint motor is connected to the inner ring of the harmonic reducer, and the stator is connected to the outer ring of the harmonic reducer; one end of the waist connector is connected to the inner ring of the harmonic reducer, and the other end is connected to the back plate; the motor rotary encoder is installed on the hip joint motor; A plurality of posture sensors are arranged on the thigh bar, the backboard, the human calf, the human thigh, the human torso, and the human upper limbs; The myoelectric sensor is arranged on the waist of the human body; A real-time controller is mounted on the back panel; the real-time controller is electrically connected to the hip joint motor, the motor rotary encoder, the posture sensor, and the myoelectric sensor; Characterized in that the adaptive robust force control method comprises the following steps: S1, initializing the sampling period of the real-time controller; initializing a number of the posture sensors and the electromyographic sensors, and adjusting the sensor values ​​to zero; rotating the thigh bar and the backboard to a vertical position, and initializing the motor rotary encoder and adjusting the motor rotary encoder value to zero; S2, establishing a physical model of the waist-assisted exoskeleton, and converting the physical model into a state equation; wherein the physical model includes a human-exoskeleton coupling system dynamics model, a human-machine interface model, and a complete constraint model provided by the wearer; S3, obtaining the angle, angular velocity, angular acceleration of each joint of the human body, and the torque at the human hip joint, obtaining the angle, angular velocity, and angular acceleration of the exoskeleton hip joint, and calculating the motor driving torque; S4, converting the motor driving torque into a control current of a corresponding hip joint motor, controlling the output torque of the corresponding hip joint motor by the control current, driving the thigh rod to rotate relative to the back plate, and realizing the movement of the waist-assisted exoskeleton; In S2, the human-exoskeleton coupling system dynamics model is: Where q = [q1 q2 q3 q4 q5] T , q1, q2, q3, q4, and q5 are the rotation angles of the human ankle joint, human knee joint, human hip joint, human shoulder joint, and exoskeleton hip joint, respectively; τ=[τ1τ2τ3τ4τ act ] T , τ1, τ2, τ3, τ4 are the applied moments of the human ankle joint, human knee joint, human hip joint, and human shoulder joint, respectively, τ act is the driving torque of the exoskeleton hip joint; F b =[F bx F by F bz ] T is the human-machine force, F bx 、F by 、F bx They represent the components of the human-machine force in the x, y, and z directions respectively; J h ∈R 3*5 is the Jacobian matrix of the human back at the back contact point; J e ∈R 3*5 is the Jacobian matrix of the back plate at the back contact; M(q)∈R 5*5 is the inertia matrix of the human-exoskeleton coupling system; Centrifugal force and Coriolis force matrix for human-exoskeleton coupling system; G(q)∈R 5 It is the gravity matrix of the human-exoskeleton coupling system; The human-machine interface model is: Where, K = diag{K x ,K y ,K z } is the equivalent spring stiffness, K x , K y , K z Respectively represent the components of the equivalent spring stiffness in the x, y, and z directions; C=diag{C x ,C y ,C z } is the damping coefficient of the equivalent damper, C x , C y , C z They represent the components of the equivalent damper damping coefficient in the x, y, and z directions respectively; x h =[x hx x hy x hz ] T is the position of the person at the back contact point, x hx 、x hy They represent the position of the person at the back contact point in the x and y directions, respectively. hz It represents the rotation angle of the person around the z-axis at the back contact point; x e =[x ex x ey x ez ] T The position of the exoskeleton at the back contact point for the waist assistance, x ex 、x ey They represent the x and y positions of the waist-assisted exoskeleton at the back contact point, respectively. ez It represents the rotation angle of the waist-assisted exoskeleton around the z-axis at the back contact point; is the speed of the person at the back contact point, They represent the speed of the person in the x and y directions at the back contact point, represents the angular velocity of the person around the z-axis at the back contact point; The speed of the exoskeleton at the back contact point for the waist, They represent the speed of the waist-assisted exoskeleton in the x and y directions at the back contact point, It represents the angular velocity of the waist-assisted exoskeleton around the z-axis at the back contact point; Centrally model uncertainty and disturbances at the human-machine interface; The complete constraint model is: q1=q hd1 (t),q2=q hd2 (t),q3=q hd3 (t),q4=q hd4 (t); In the formula, q hd1 (t) represents the relationship between the human ankle joint angle and time t; q hd2 (t) represents the relationship between the human knee joint angle and time t; q hd3 (t) represents the relationship between the human hip joint angle and time t; q hd4 (t) represents the relationship between the human shoulder joint angle and time t; The method for converting the physical model into a state equation comprises the following steps: S5.1, calculation of τ3 and τ act relationship; S5.2, let the state variable x1 = ∫τ3dτ, and let the concentrated model uncertainty be: S5.3, the centralized model uncertainty is divided into two parts: a constant and a time-varying function, and we get Δ 1n and Δ1 represent The constant part and the time-varying part of S5.4, let θ = [J5 Y2Δ 1n K x K y K z C x C y C z ] T ; Among them, J5 and Y2 are the system parameters of the waist power-assisted exoskeleton; S5.5, the state equation of the physical model of the waist-assisted exoskeleton is constructed as follows: in, g is the acceleration due to gravity, c is 125tm =cos(q1+q2+q5-θ m ), θ m is the angle between the thigh bar and the human thigh; 2. The adaptive robust force control method of the wearable waist-assisted exoskeleton according to claim 1 is characterized in that: In S5.1, calculate τ3 and τ act The relationship methods include: The first-order and second-order derivatives of the complete constraint model are: According to the complete constraint model, the human-exoskeleton coupling system dynamics model and the human-machine interface model, we can find τ3 is: Where M 51 ,M 52 ,M 53 ,M 54 ,M 55 They are the corresponding elements of the 5th row and 1st to 5th columns in M(q), U5 = [00001], U3 = [00100]; Transform the above formula and Substituting in, we get: In the formula, M 31 ,M 32 ,M 33 ,M 34 They are the corresponding elements in the 3rd row and 1st to 4th columns in M(q); C 31 ,C 32 ,C 33 ,C 34 They are The corresponding elements in the 3rd row, 1st to 4th columns; C 51 ,C 52 They are The corresponding elements in the 5th row, 1st to 2nd columns; G3 and G5 are the corresponding elements in the 3rd and 5th rows of G(q) respectively.

3. The adaptive robust force control method of the wearable waist-assisted exoskeleton according to claim 2 is characterized in that: In S3, the method for calculating the motor driving torque includes: According to the state equation of the physical model of the waist-assisted exoskeleton, the control error is z1=x1-x 1d , where x 1d is the integral of the expected human hip moment; The motor driving torque is equal to τ act , the control objective is to design τ act Make z1 approach 0; Assume τ act =τ acta +τ acts ,in τ acts =k1z1+τ actsn , is the desired human hip torque, k1 represents the gain value of linear feedback, τ actsn is the nonlinear feedback term; is an estimate of the actual value θ, and the estimated value The range is: for The minimum value of for The maximum value of Adaptive Rate get: in Γ1 is the adaptation rate matrix, The mapping function is: In the formula, i is the independent variable; τ actsn Two conditions must be met: In the formula, ε1 is a threshold and is any non-negative number.

4. An adaptive robust force control device for a wearable waist-assisted exoskeleton, characterized in that: An adaptive robust force control method for a wearable waist-assisted exoskeleton as claimed in any one of claims 1 to 3 is used; The adaptive robust force control device of the wearable waist-assisted exoskeleton comprises: An initialization module, comprising submodule 1, submodule 2, submodule 3, and submodule 4; the submodule 1 is used to initialize the sampling period of the real-time controller; the submodule 2 is used to initialize a plurality of the posture sensors and adjust the posture sensor values ​​to zero; the submodule 3 is used to rotate the thigh bar and the back plate to a vertical position, and initialize the motor rotary encoder and adjust the motor rotary encoder value to zero; the submodule 4 is used to initialize the electromyographic sensor and adjust the electromyographic sensor value to zero; A model building module, which is used to build a physical model of the waist-assisted exoskeleton and convert the physical model into a state equation; wherein the physical model includes a human-exoskeleton coupling dynamics model, a human-machine interface model, and a complete constraint model provided by the wearer; The data acquisition and processing module is used to obtain the angle, angular velocity, angular acceleration of each joint of the human body, and the torque at the human hip joint, obtain the angle, angular velocity, angular acceleration of the exoskeleton hip joint, and calculate the motor driving torque; A conversion module, which is used to convert the motor driving torque into a control current of a corresponding hip joint motor; The output module is used to control the output torque of the corresponding hip joint motor through the control current, drive the thigh rod to rotate relative to the back plate, and realize the movement of the waist-assisted exoskeleton.

5. A computer terminal comprising a memory, a processor and a computer program in the memory that can be run on the processor, characterized in that: When the processor executes the program, the adaptive robust force control method of the wearable waist-assisted exoskeleton as described in any one of claims 1 to 4 is implemented.

6. A readable storage medium, characterized in that: The readable storage medium stores computer program instructions, and when the computer program instructions are read and executed by a processor, the adaptive robust force control method of the wearable waist-assisted exoskeleton as described in any one of claims 1 to 4 is executed.

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